Multimodal Scene Understanding

Multimodal Scene Understanding
Author: Michael Ying Yang,Bodo Rosenhahn,Vittorio Murino
Publsiher: Academic Press
Total Pages: 422
Release: 2019-07-16
ISBN 10: 0128173599
ISBN 13: 9780128173596
Language: EN, FR, DE, ES & NL

Multimodal Scene Understanding Book Review:

Multimodal Scene Understanding: Algorithms, Applications and Deep Learning presents recent advances in multi-modal computing, with a focus on computer vision and photogrammetry. It provides the latest algorithms and applications that involve combining multiple sources of information and describes the role and approaches of multi-sensory data and multi-modal deep learning. The book is ideal for researchers from the fields of computer vision, remote sensing, robotics, and photogrammetry, thus helping foster interdisciplinary interaction and collaboration between these realms. Researchers collecting and analyzing multi-sensory data collections – for example, KITTI benchmark (stereo+laser) - from different platforms, such as autonomous vehicles, surveillance cameras, UAVs, planes and satellites will find this book to be very useful. Contains state-of-the-art developments on multi-modal computing Shines a focus on algorithms and applications Presents novel deep learning topics on multi-sensor fusion and multi-modal deep learning

Multimodal Computational Attention for Scene Understanding and Robotics

Multimodal Computational Attention for Scene Understanding and Robotics
Author: Boris Schauerte
Publsiher: Springer
Total Pages: 203
Release: 2016-05-11
ISBN 10: 3319337963
ISBN 13: 9783319337968
Language: EN, FR, DE, ES & NL

Multimodal Computational Attention for Scene Understanding and Robotics Book Review:

This book presents state-of-the-art computational attention models that have been successfully tested in diverse application areas and can build the foundation for artificial systems to efficiently explore, analyze, and understand natural scenes. It gives a comprehensive overview of the most recent computational attention models for processing visual and acoustic input. It covers the biological background of visual and auditory attention, as well as bottom-up and top-down attentional mechanisms and discusses various applications. In the first part new approaches for bottom-up visual and acoustic saliency models are presented and applied to the task of audio-visual scene exploration of a robot. In the second part the influence of top-down cues for attention modeling is investigated.

Multi Modal Scene Understanding for Robotic Grasping

Multi Modal Scene Understanding for Robotic Grasping
Author: Jeannette Bohg
Publsiher: Unknown
Total Pages: 329
Release: 2011
ISBN 10:
ISBN 13: OCLC:951145279
Language: EN, FR, DE, ES & NL

Multi Modal Scene Understanding for Robotic Grasping Book Review:

Machine Learning for Multimodal Interaction

Machine Learning for Multimodal Interaction
Author: Andrei Popescu-Belis,Steve Renals,Hervé Bourlard
Publsiher: Springer
Total Pages: 308
Release: 2008-02-22
ISBN 10: 3540781552
ISBN 13: 9783540781554
Language: EN, FR, DE, ES & NL

Machine Learning for Multimodal Interaction Book Review:

This book constitutes the thoroughly refereed post-proceedings of the 4th International Workshop on Machine Learning for Multimodal Interaction, MLMI 2007, held in Brno, Czech Republic, in June 2007. The 25 revised full papers presented together with 1 invited paper were carefully selected during two rounds of reviewing and revision from 60 workshop presentations. The papers are organized in topical sections on multimodal processing, HCI, user studies and applications, image and video processing, discourse and dialogue processing, speech and audio processing, as well as the PASCAL speech separation challenge.

Multimodal Behavior Analysis in the Wild

Multimodal Behavior Analysis in the Wild
Author: Xavier Alameda-Pineda,Elisa Ricci,Nicu Sebe
Publsiher: Academic Press
Total Pages: 498
Release: 2018-11-13
ISBN 10: 0128146028
ISBN 13: 9780128146026
Language: EN, FR, DE, ES & NL

Multimodal Behavior Analysis in the Wild Book Review:

Multimodal Behavioral Analysis in the Wild: Advances and Challenges presents the state-of- the-art in behavioral signal processing using different data modalities, with a special focus on identifying the strengths and limitations of current technologies. The book focuses on audio and video modalities, while also emphasizing emerging modalities, such as accelerometer or proximity data. It covers tasks at different levels of complexity, from low level (speaker detection, sensorimotor links, source separation), through middle level (conversational group detection, addresser and addressee identification), and high level (personality and emotion recognition), providing insights on how to exploit inter-level and intra-level links. This is a valuable resource on the state-of-the- art and future research challenges of multi-modal behavioral analysis in the wild. It is suitable for researchers and graduate students in the fields of computer vision, audio processing, pattern recognition, machine learning and social signal processing. Gives a comprehensive collection of information on the state-of-the-art, limitations, and challenges associated with extracting behavioral cues from real-world scenarios Presents numerous applications on how different behavioral cues have been successfully extracted from different data sources Provides a wide variety of methodologies used to extract behavioral cues from multi-modal data

2016 International Symposium on Experimental Robotics

2016 International Symposium on Experimental Robotics
Author: Dana Kulić,Yoshihiko Nakamura,Oussama Khatib,Gentiane Venture
Publsiher: Springer
Total Pages: 856
Release: 2017-03-20
ISBN 10: 3319501151
ISBN 13: 9783319501154
Language: EN, FR, DE, ES & NL

2016 International Symposium on Experimental Robotics Book Review:

Experimental Robotics XV is the collection of papers presented at the International Symposium on Experimental Robotics, Roppongi, Tokyo, Japan on October 3-6, 2016. 73 scientific papers were selected and presented after peer review. The papers span a broad range of sub-fields in robotics including aerial robots, mobile robots, actuation, grasping, manipulation, planning and control and human-robot interaction, but shared cutting-edge approaches and paradigms to experimental robotics. The readers will find a breadth of new directions of experimental robotics. The International Symposium on Experimental Robotics is a series of bi-annual symposia sponsored by the International Foundation of Robotics Research, whose goal is to provide a forum dedicated to experimental robotics research. Robotics has been widening its scientific scope, deepening its methodologies and expanding its applications. However, the significance of experiments remains and will remain at the center of the discipline. The ISER gatherings are a venue where scientists can gather and talk about robotics based on this central tenet.

Pattern Recognition and Computer Vision

Pattern Recognition and Computer Vision
Author: Zhouchen Lin,Liang Wang,Jian Yang,Guangming Shi,Tieniu Tan,Nanning Zheng,Xilin Chen,Yanning Zhang
Publsiher: Springer Nature
Total Pages: 813
Release: 2019-10-31
ISBN 10: 3030317234
ISBN 13: 9783030317232
Language: EN, FR, DE, ES & NL

Pattern Recognition and Computer Vision Book Review:

The three-volume set LNCS 11857, 11858, and 11859 constitutes the refereed proceedings of the Second Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2019, held in Xi’an, China, in November 2019. The 165 revised full papers presented were carefully reviewed and selected from 412 submissions. The papers have been organized in the following topical sections: Part I: Object Detection, Tracking and Recognition, Part II: Image/Video Processing and Analysis, Part III: Data Analysis and Optimization.

International Conference on Multimodal Interfaces

International Conference on Multimodal Interfaces
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2006
ISBN 10:
ISBN 13: UOM:39015058904395
Language: EN, FR, DE, ES & NL

International Conference on Multimodal Interfaces Book Review:

Handbook of Deep Learning Applications

Handbook of Deep Learning Applications
Author: Valentina Emilia Balas,Sanjiban Sekhar Roy,Dharmendra Sharma,Pijush Samui
Publsiher: Springer
Total Pages: 383
Release: 2019-02-25
ISBN 10: 3030114791
ISBN 13: 9783030114794
Language: EN, FR, DE, ES & NL

Handbook of Deep Learning Applications Book Review:

This book presents a broad range of deep-learning applications related to vision, natural language processing, gene expression, arbitrary object recognition, driverless cars, semantic image segmentation, deep visual residual abstraction, brain–computer interfaces, big data processing, hierarchical deep learning networks as game-playing artefacts using regret matching, and building GPU-accelerated deep learning frameworks. Deep learning, an advanced level of machine learning technique that combines class of learning algorithms with the use of many layers of nonlinear units, has gained considerable attention in recent times. Unlike other books on the market, this volume addresses the challenges of deep learning implementation, computation time, and the complexity of reasoning and modeling different type of data. As such, it is a valuable and comprehensive resource for engineers, researchers, graduate students and Ph.D. scholars.

Group and Crowd Behavior for Computer Vision

Group and Crowd Behavior for Computer Vision
Author: Vittorio Murino,Marco Cristani,Shishir Shah,Silvio Savarese
Publsiher: Academic Press
Total Pages: 438
Release: 2017-04-18
ISBN 10: 0128092807
ISBN 13: 9780128092804
Language: EN, FR, DE, ES & NL

Group and Crowd Behavior for Computer Vision Book Review:

Group and Crowd Behavior for Computer Vision provides a multidisciplinary perspective on how to solve the problem of group and crowd analysis and modeling, combining insights from the social sciences with technological ideas in computer vision and pattern recognition. The book answers many unresolved issues in group and crowd behavior, with Part One providing an introduction to the problems of analyzing groups and crowds that stresses that they should not be considered as completely diverse entities, but as an aggregation of people. Part Two focuses on features and representations with the aim of recognizing the presence of groups and crowds in image and video data. It discusses low level processing methods to individuate when and where a group or crowd is placed in the scene, spanning from the use of people detectors toward more ad-hoc strategies to individuate group and crowd formations. Part Three discusses methods for analyzing the behavior of groups and the crowd once they have been detected, showing how to extract semantic information, predicting/tracking the movement of a group, the formation or disaggregation of a group/crowd and the identification of different kinds of groups/crowds depending on their behavior. The final section focuses on identifying and promoting datasets for group/crowd analysis and modeling, presenting and discussing metrics for evaluating the pros and cons of the various models and methods. This book gives computer vision researcher techniques for segmentation and grouping, tracking and reasoning for solving group and crowd modeling and analysis, as well as more general problems in computer vision and machine learning. Presents the first book to cover the topic of modeling and analysis of groups in computer vision Discusses the topics of group and crowd modeling from a cross-disciplinary perspective, using social science anthropological theories translated into computer vision algorithms Focuses on group and crowd analysis metrics Discusses real industrial systems dealing with the problem of analyzing groups and crowds

Handbook of Neural Computation

Handbook of Neural Computation
Author: Pijush Samui,Sanjiban Sekhar Roy,Valentina E. Balas
Publsiher: Academic Press
Total Pages: 658
Release: 2017-07-18
ISBN 10: 0128113197
ISBN 13: 9780128113196
Language: EN, FR, DE, ES & NL

Handbook of Neural Computation Book Review:

Handbook of Neural Computation explores neural computation applications, ranging from conventional fields of mechanical and civil engineering, to electronics, electrical engineering and computer science. This book covers the numerous applications of artificial and deep neural networks and their uses in learning machines, including image and speech recognition, natural language processing and risk analysis. Edited by renowned authorities in this field, this work is comprised of articles from reputable industry and academic scholars and experts from around the world. Each contributor presents a specific research issue with its recent and future trends. As the demand rises in the engineering and medical industries for neural networks and other machine learning methods to solve different types of operations, such as data prediction, classification of images, analysis of big data, and intelligent decision-making, this book provides readers with the latest, cutting-edge research in one comprehensive text. Features high-quality research articles on multivariate adaptive regression splines, the minimax probability machine, and more Discusses machine learning techniques, including classification, clustering, regression, web mining, information retrieval and natural language processing Covers supervised, unsupervised, reinforced, ensemble, and nature-inspired learning methods

Multimodal Processing and Interaction

Multimodal Processing and Interaction
Author: Petros Maragos,Alexandros Potamianos,Patrick Gros
Publsiher: Springer Science & Business Media
Total Pages: 374
Release: 2008-12-16
ISBN 10: 9780387763163
ISBN 13: 0387763163
Language: EN, FR, DE, ES & NL

Multimodal Processing and Interaction Book Review:

This volume presents high quality, state-of-the-art research ideas and results from theoretic, algorithmic and application viewpoints. It contains contributions by leading experts in the obsequious scientific and technological field of multimedia. The book specifically focuses on interaction with multimedia content with special emphasis on multimodal interfaces for accessing multimedia information. The book is designed for a professional audience composed of practitioners and researchers in industry. It is also suitable for advanced-level students in computer science.

Sensor Based Intelligent Robots

Sensor Based Intelligent Robots
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2000
ISBN 10:
ISBN 13: UOM:39015048324209
Language: EN, FR, DE, ES & NL

Sensor Based Intelligent Robots Book Review:

Deep Learning with Python

Deep Learning with Python
Author: Francois Chollet
Publsiher: Manning Publications
Total Pages: 384
Release: 2017-10-28
ISBN 10: 9781617294433
ISBN 13: 1617294438
Language: EN, FR, DE, ES & NL

Deep Learning with Python Book Review:

Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran�ois Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning--a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher Fran�ois Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author Fran�ois Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Sounding Composition

Sounding Composition
Author: Steph Ceraso
Publsiher: University of Pittsburgh Press
Total Pages: 176
Release: 2018-07-20
ISBN 10: 0822983443
ISBN 13: 9780822983446
Language: EN, FR, DE, ES & NL

Sounding Composition Book Review:

In Sounding Composition Steph Ceraso reimagines listening education to account for twenty-first-century sonic practices and experiences. Sonic technologies such as audio editing platforms and music software allow students to control sound in ways that were not always possible for the average listener. While digital technologies have presented new opportunities for teaching listening in relation to composing, they also have resulted in a limited understanding of how sound works in the world at large. Ceraso offers an expansive approach to sonic pedagogy through the concept of multimodal listening—a practice that involves developing an awareness of how sound shapes and is shaped by different contexts, material objects, and bodily, multisensory experiences. Through a mix of case studies and pedagogical materials, she demonstrates how multimodal listening enables students to become more savvy consumers and producers of sound in relation to composing digital media, and in their everyday lives.

Proceedings

Proceedings
Author: American Association for Artificial Intelligence
Publsiher: Menlo Park, Calif. : AAAI Press ; MIT Press
Total Pages: 1034
Release: 2002
ISBN 10: 9780262511292
ISBN 13: 0262511290
Language: EN, FR, DE, ES & NL

Proceedings Book Review:

The annual AAAI National Conference provides a forum for information exchange and interaction among researchers from all disciplines of AI. Contributions include theoretical, experimental and empirical results. Topics cover principles of cognition, perception and action; the design, application and evaluation of AI algorithms and systems; architectures and frameworks for classses of AI systems; and analyses of tasks and domains in which intelligent systems perform. The Innovative Applications Conference highlights successful application of AI technology and explores issues, methods and lessons learned in the development and deployment of AI applications.

Proceedings

Proceedings
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2002
ISBN 10:
ISBN 13: UOM:39015048321874
Language: EN, FR, DE, ES & NL

Proceedings Book Review:

Multimodal Surveillance

Multimodal Surveillance
Author: Dr. Zhigang Zhu,Thomas S. Huang
Publsiher: Artech House Publishers
Total Pages: 428
Release: 2007
ISBN 10:
ISBN 13: STANFORD:36105123309374
Language: EN, FR, DE, ES & NL

Multimodal Surveillance Book Review:

This resource brings together the multimodal surveillance fields leading experts, who guide researchers, designers, engineers, and developers through this multifaceted technology. It discusses the latest high-end sensors for extremely accurate surveillance, as well as low-cost sensing solutions.

Deep Learning

Deep Learning
Author: Ian Goodfellow,Yoshua Bengio,Aaron Courville
Publsiher: MIT Press
Total Pages: 800
Release: 2016-11-10
ISBN 10: 0262337371
ISBN 13: 9780262337373
Language: EN, FR, DE, ES & NL

Deep Learning Book Review:

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

The Technology of Binaural Understanding

The Technology of Binaural Understanding
Author: Jens Blauert,Jonas Braasch
Publsiher: Springer Nature
Total Pages: 815
Release: 2020-08-12
ISBN 10: 3030003868
ISBN 13: 9783030003869
Language: EN, FR, DE, ES & NL

The Technology of Binaural Understanding Book Review:

Sound, devoid of meaning, would not matter to us. It is the information sound conveys that helps the brain to understand its environment. Sound and its underlying meaning are always associated with time and space. There is no sound without spatial properties, and the brain always organizes this information within a temporal–spatial framework. This book is devoted to understanding the importance of meaning for spatial and related further aspects of hearing, including cross-modal inference. People, when exposed to acoustic stimuli, do not react directly to what they hear but rather to what they hear means to them. This semiotic maxim may not always apply, for instance, when the reactions are reflexive. But, where it does apply, it poses a major challenge to the builders of models of the auditory system. Take, for example, an auditory model that is meant to be implemented on a robotic agent for autonomous search-&-rescue actions. Or think of a system that can perform judgments on the sound quality of multimedia-reproduction systems. It becomes immediately clear that such a system needs • Cognitive capabilities, including substantial inherent knowledge • The ability to integrate information across different sensory modalities To realize these functions, the auditory system provides a pair of sensory organs, the two ears, and the means to perform adequate preprocessing of the signals provided by the ears. This is realized in the subcortical parts of the auditory system. In the title of a prior book, the term Binaural Listening is used to indicate a focus on sub-cortical functions. Psychoacoustics and auditory signal processing contribute substantially to this area. The preprocessed signals are then forwarded to the cortical parts of the auditory system where, among other things, recognition, classification, localization, scene analysis, assignment of meaning, quality assessment, and action planning take place. Also, information from different sensory modalities is integrated at this level. Between sub-cortical and cortical regions of the auditory system, numerous feedback loops exist that ultimately support the high complexity and plasticity of the auditory system. The current book concentrates on these cognitive functions. Instead of processing signals, processing symbols is now the predominant modeling task. Substantial contributions to the field draw upon the knowledge acquired by cognitive psychology. The keyword Binaural Understanding in the book title characterizes this shift. Both books, The Technology of Binaural Listening and the current one, have been stimulated and supported by AABBA, an open research group devoted to the development and application of models of binaural hearing. The current book is dedicated to technologies that help explain, facilitate, apply, and support various aspects of binaural understanding. It is organized into five parts, each containing three to six chapters in order to provide a comprehensive overview of this emerging area. Each chapter was thoroughly reviewed by at least two anonymous, external experts. The first part deals with the psychophysical and physiological effects of Forming and Interpreting Aural Objects as well as the underlying models. The fundamental concepts of reflexive and reflective auditory feedback are introduced. Mechanisms of binaural attention and attention switching are covered—as well as how auditory Gestalt rules facilitate binaural understanding. A general blackboard architecture is introduced as an example of how machines can learn to form and interpret aural objects to simulate human cognitive listening. The second part, Configuring and Understanding Aural Space, focuses on the human understanding of complex three-dimensional environments—covering the psychological and biological fundamentals of auditory space formation. This part further addresses the human mechanisms used to process information and interact in complex reverberant environments, such as concert halls and forests, and additionally examines how the auditory system can learn to understand and adapt to these environments. The third part is dedicated to Processing Cross-Modal Inference and highlights the fundamental human mechanisms used to integrate auditory cues with cues from other modalities to localize and form perceptual objects. This part also provides a general framework for understanding how complex multimodal scenes can be simulated and rendered. The fourth part, Evaluating Aural-scene Quality and Speech Understanding, focuses on the object-forming aspects of binaural listening and understanding. It addresses cognitive mechanisms involved in both the understanding of speech and the processing of nonverbal information such as Sound Quality and Quality-of- Experience. The aesthetic judgment of rooms is also discussed in this context. Models that simulate underlying human processes and performance are covered in addition to techniques for rendering virtual environments that can then be used to test these models. The fifth part deals with the Application of Cognitive Mechanisms to Audio Technology. It highlights how cognitive mechanisms can be utilized to create spatial auditory illusions using binaural and other 3D-audio technologies. Further, it covers how cognitive binaural technologies can be applied to improve human performance in auditory displays and to develop new auditory technologies for interactive robots. The book concludes with the application of cognitive binaural technologies to the next generation of hearing aids.